We consider the online scheduling problem of minimizing total weighted flow time plus energy in the dynamic speed scaling model, where a processor can scale its speed dynamically between 0 and some maximum speed T. In the past few years this problem has been studied extensively under the clairvoyant setting, which requires the size of a job to be known at release time [AlF07,BPS07,BCL+08,LLT+esa08,LLT+spaa08,BCP09,GNS09,LLT+09]. For the non-clairvoyant setting, despite its practical importance, the progress is relatively limited. Only recently an online algorithm [LAPS] is known to be O(1)-competitive for minimizing (unweighted) flow time plus energy in the infinite speed model (i.e., T = ∞) [CEL+09,CEP09]. This paper makes two contributions to the non-clairvoyant scheduling. First, we resolve the open problem that the unweighted result of [LAPS] can be extended to the more realistic model with bounded maximum speed. Second, we show that another non-clairvoyant algorithm [WRR] is O(1)-competitive when weighted flow time is concerned. Note that [WRR] is not as efficient as [LAPS] for scheduling unweighted jobs as [WRR] has a much bigger constant hidden in its competitive ratio.